Tim Klas Kraska Manning Assistant Professor of Computer Science

Currently, my research focuses on Big Data management andhybrid human/machine database systems. Before joining Brown, I spent 2 years as a PostDoc in the AMP Lab at UC Berkeley after receiving my PhD from ETH Zurich. At ETH, I was part of the Systems Group, where I worked on transaction management and stream processing in the cloud. I co-authored one of the first works taking a data management perspective on cloud computing and the first research paper on hybrid human/machine database systems. I received a Swiss National Science Foundation Prospective Researcher Fellowship (2010), a DAAD Scholarship (2006), a University of Sydney Master of Information Technology Scholarship for outstanding achievement (2005), the University of Sydney Siemens Prize (2005), a VLDB best demo award (2011) and ICDE best paper award.

Brown Affiliations

Research Areas

research overview

Tim Kraska conducts research on the design and implementation of highly scalable data management solutions. His recent work focusses on simplifying the use of machine learning on a single machine as well as at scale on hundreds/thousands of machines, distributed replication across data centers using Paxos, OLTP and OLAP database systems, and building hybrid human/machine systems, which automatically incorporate the knowledge of people using crowd-sourcing.

research statement

In the following a list of my current and past research projects:


  • MLBase - The Distributed Machine-Learning Management System

  • CrowdQ - Crowdsourced Query Understanding

  • MDCC - The Fastest Strong Consistent Multi-Data Center Replication Protocol

  • CrowdDB - Answering Queries with Crowdsourcing

  • PIQL - Performance Insightful Query Language

  • Cloudy/Smoky - a distributed storage and streaming service in the cloud

  • Building a database on cloud infrastructure

  • CloudBench - a benchmark for the cloud

  • Zorba - a general purpose XQuery processor implementing in C++

  • MXQuery - A lightweight, full-featured Java XQuery Engine

  • Mapping Data to Queries (MDQ) - data integration with XQuery

  • XQIB - XQuery In the Browser